AI Guidance Helps Novices Perform Echocardiography
By MedImaging International staff writers Posted on 09 Mar 2021 |

Image: Using AI technology, novice staff can acquire quality ultrasounds (Photo courtesy of Dreamstime)
Nurses with no training in ultrasound were able to acquire diagnostic-quality images by using an artificial intelligence (AI)-based software application, according to a new study.
Researchers at Northwestern University (NU; Evanston, IL, USA), MedStar Washington Hospital Center (Washington, DC, USA), and other institutions conducted a prospective, multicenter diagnostic study involving eight nurses with no experience in ultrasound. The nurses were then trained using Caption Guidance, a deep-learning (DL) algorithm developed by Caption Health (Brisbane, CA, USA) that provides real-time prescriptive guidance for limited diagnostic transthoracic echocardiographic scans.
Each nurse scanned 10-view transthoracic echocardiograms in 30 patients, which were then compared with those of level 3-trained technicians using the same hardware, but without AI guidance. The results showed that the novice nurses produced echocardiograms judged to be of diagnostic quality for left ventricular size, function, and pericardial effusion in 98.8% of the scans, and right ventricular size in 92.5%. Experienced sonographers, however, were much better at determining the size of the inferior vena cava (91.5% versus 57.4%). The study was published on February 18, 2021, in JAMA Cardiology.
“The ability to provide echocardiography outside the traditional laboratory setting is largely limited by a lack of trained sonographers and cardiologists to acquire and interpret images,” concluded senior author cardiologist James Thomas, MD, of Northwestern University, and colleagues. “Using this AI-based technology, individuals with no previous training may be able to obtain diagnostic echocardiographic clips of several key cardiac parameters.”
“In our mission to democratize access to healthcare and quality medical imaging, we wanted to ensure that we tested Caption Guidance on a wide range of patients to prove its effectiveness across a diverse population,” said Yngvil Thomas, head of medical affairs and clinical development at Caption Health. “This study shows that AI-guided imaging can expand healthcare professionals’ skill sets in a meaningful way with minimal training, giving patients more opportunities to receive timely diagnostic care.”
Related Links:
Northwestern University
MedStar Washington Hospital Center
Caption Health
Researchers at Northwestern University (NU; Evanston, IL, USA), MedStar Washington Hospital Center (Washington, DC, USA), and other institutions conducted a prospective, multicenter diagnostic study involving eight nurses with no experience in ultrasound. The nurses were then trained using Caption Guidance, a deep-learning (DL) algorithm developed by Caption Health (Brisbane, CA, USA) that provides real-time prescriptive guidance for limited diagnostic transthoracic echocardiographic scans.
Each nurse scanned 10-view transthoracic echocardiograms in 30 patients, which were then compared with those of level 3-trained technicians using the same hardware, but without AI guidance. The results showed that the novice nurses produced echocardiograms judged to be of diagnostic quality for left ventricular size, function, and pericardial effusion in 98.8% of the scans, and right ventricular size in 92.5%. Experienced sonographers, however, were much better at determining the size of the inferior vena cava (91.5% versus 57.4%). The study was published on February 18, 2021, in JAMA Cardiology.
“The ability to provide echocardiography outside the traditional laboratory setting is largely limited by a lack of trained sonographers and cardiologists to acquire and interpret images,” concluded senior author cardiologist James Thomas, MD, of Northwestern University, and colleagues. “Using this AI-based technology, individuals with no previous training may be able to obtain diagnostic echocardiographic clips of several key cardiac parameters.”
“In our mission to democratize access to healthcare and quality medical imaging, we wanted to ensure that we tested Caption Guidance on a wide range of patients to prove its effectiveness across a diverse population,” said Yngvil Thomas, head of medical affairs and clinical development at Caption Health. “This study shows that AI-guided imaging can expand healthcare professionals’ skill sets in a meaningful way with minimal training, giving patients more opportunities to receive timely diagnostic care.”
Related Links:
Northwestern University
MedStar Washington Hospital Center
Caption Health
Latest Ultrasound News
- Non-Invasive Ultrasound-Based Tool Accurately Detects Infant Meningitis
- Breakthrough Deep Learning Model Enhances Handheld 3D Medical Imaging
- Pain-Free Breast Imaging System Performs One Minute Cancer Scan
- Wireless Chronic Pain Management Device to Reduce Need for Painkillers and Surgery
- New Medical Ultrasound Imaging Technique Enables ICU Bedside Monitoring
- New Incision-Free Technique Halts Growth of Debilitating Brain Lesions
- AI-Powered Lung Ultrasound Outperforms Human Experts in Tuberculosis Diagnosis
- AI Identifies Heart Valve Disease from Common Imaging Test
- Novel Imaging Method Enables Early Diagnosis and Treatment Monitoring of Type 2 Diabetes
- Ultrasound-Based Microscopy Technique to Help Diagnose Small Vessel Diseases
- Smart Ultrasound-Activated Immune Cells Destroy Cancer Cells for Extended Periods
- Tiny Magnetic Robot Takes 3D Scans from Deep Within Body
- High Resolution Ultrasound Speeds Up Prostate Cancer Diagnosis
- World's First Wireless, Handheld, Whole-Body Ultrasound with Single PZT Transducer Makes Imaging More Accessible
- Artificial Intelligence Detects Undiagnosed Liver Disease from Echocardiograms
- Ultrasound Imaging Non-Invasively Tracks Tumor Response to Radiation and Immunotherapy
Channels
Radiography
view channel
AI Hybrid Strategy Improves Mammogram Interpretation
Breast cancer screening programs rely heavily on radiologists interpreting mammograms, a process that is time-intensive and subject to errors. While artificial intelligence (AI) models have shown strong... Read more
AI Technology Predicts Personalized Five-Year Risk of Developing Breast Cancer
Breast cancer remains one of the most common cancers among women, with about one in eight receiving a diagnosis in their lifetime. Despite widespread use of mammography, about 34% of patients in the U.... Read moreMRI
view channel
AI-Assisted Model Enhances MRI Heart Scans
A cardiac MRI can reveal critical information about the heart’s function and any abnormalities, but traditional scans take 30 to 90 minutes and often suffer from poor image quality due to patient movement.... Read more
AI Model Outperforms Doctors at Identifying Patients Most At-Risk of Cardiac Arrest
Hypertrophic cardiomyopathy is one of the most common inherited heart conditions and a leading cause of sudden cardiac death in young individuals and athletes. While many patients live normal lives, some... Read moreNuclear Medicine
view channel
New Camera Sees Inside Human Body for Enhanced Scanning and Diagnosis
Nuclear medicine scans like single-photon emission computed tomography (SPECT) allow doctors to observe heart function, track blood flow, and detect hidden diseases. However, current detectors are either... Read more
Novel Bacteria-Specific PET Imaging Approach Detects Hard-To-Diagnose Lung Infections
Mycobacteroides abscessus is a rapidly growing mycobacteria that primarily affects immunocompromised patients and those with underlying lung diseases, such as cystic fibrosis or chronic obstructive pulmonary... Read moreGeneral/Advanced Imaging
view channel
Cutting-Edge Angio-CT Solution Offers New Therapeutic Possibilities
Maintaining accuracy and safety in interventional radiology is a constant challenge, especially as complex procedures require both high precision and efficiency. Traditional setups often involve multiple... Read more
Extending CT Imaging Detects Hidden Blood Clots in Stroke Patients
Strokes caused by blood clots or other mechanisms that obstruct blood flow in the brain account for about 85% of all strokes. Determining where a clot originates is crucial, since it guides safe and effective... Read more
Groundbreaking AI Model Accurately Segments Liver Tumors from CT Scans
Liver cancer is the sixth most common cancer worldwide and a leading cause of cancer-related deaths. Accurate segmentation of liver tumors is critical for diagnosis and therapy, but manual methods by radiologists... Read more
New CT-Based Indicator Helps Predict Life-Threatening Postpartum Bleeding Cases
Postpartum hemorrhage (PPH) is a leading cause of maternal death worldwide. While most cases can be controlled with medications and basic interventions, some become life-threatening and require invasive treatments.... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more